Kangping Chen

1.1k total citations
32 papers, 876 citations indexed

About

Kangping Chen is a scholar working on Computational Mechanics, Mechanical Engineering and Fluid Flow and Transfer Processes. According to data from OpenAlex, Kangping Chen has authored 32 papers receiving a total of 876 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Mechanics, 10 papers in Mechanical Engineering and 9 papers in Fluid Flow and Transfer Processes. Recurrent topics in Kangping Chen's work include Fluid Dynamics and Thin Films (10 papers), Rheology and Fluid Dynamics Studies (9 papers) and Fluid Dynamics and Turbulent Flows (6 papers). Kangping Chen is often cited by papers focused on Fluid Dynamics and Thin Films (10 papers), Rheology and Fluid Dynamics Studies (9 papers) and Fluid Dynamics and Turbulent Flows (6 papers). Kangping Chen collaborates with scholars based in United States, China and United Kingdom. Kangping Chen's co-authors include Daniel D. Joseph, Luigi Preziosi, D. D. Joseph, Yang Xia, Yuanyuan Wang, Biao Tang, Hucheng Deng, Yong Deng, Yuxuan Tang and Qing Li and has published in prestigious journals such as Analytical Chemistry, Journal of Fluid Mechanics and IEEE Access.

In The Last Decade

Kangping Chen

31 papers receiving 847 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kangping Chen United States 16 479 265 212 203 156 32 876
Rekha R. Rao United States 15 393 0.8× 130 0.5× 202 1.0× 147 0.7× 93 0.6× 52 821
M. M. Chen United States 14 350 0.7× 324 1.2× 291 1.4× 45 0.2× 106 0.7× 23 774
Adam Powell United States 16 198 0.4× 370 1.4× 114 0.5× 200 1.0× 38 0.2× 51 907
G.H. Evans United States 17 680 1.4× 156 0.6× 116 0.5× 412 2.0× 61 0.4× 33 1.1k
Zhang Xian China 8 152 0.3× 201 0.8× 176 0.8× 21 0.1× 89 0.6× 11 589
William J. Milliken United States 18 401 0.8× 387 1.5× 134 0.6× 191 0.9× 562 3.6× 41 1.2k
Vanessa Magnanimo Netherlands 17 671 1.4× 171 0.6× 76 0.4× 40 0.2× 108 0.7× 61 1.0k
Jeferson Ávila Souza Brazil 15 143 0.3× 240 0.9× 83 0.4× 15 0.1× 156 1.0× 86 631
André Bieberle Germany 20 341 0.7× 301 1.1× 695 3.3× 22 0.1× 159 1.0× 71 1.0k
Mingfei Lu China 17 360 0.8× 269 1.0× 93 0.4× 386 1.9× 18 0.1× 49 1.1k

Countries citing papers authored by Kangping Chen

Since Specialization
Citations

This map shows the geographic impact of Kangping Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kangping Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kangping Chen more than expected).

Fields of papers citing papers by Kangping Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kangping Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kangping Chen. The network helps show where Kangping Chen may publish in the future.

Co-authorship network of co-authors of Kangping Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Kangping Chen. A scholar is included among the top collaborators of Kangping Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kangping Chen. Kangping Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhao, Hong, et al.. (2025). Optimizing the flexible job shop scheduling problem via deep reinforcement learning with mean multichannel graph attention. Applied Soft Computing. 177. 113128–113128. 1 indexed citations
4.
Zhao, Hong, et al.. (2024). A deep reinforcement learning method based on a multiexpert graph neural network for flexible job shop scheduling. Computers & Industrial Engineering. 200. 110768–110768. 8 indexed citations
5.
Zhao, Hong, et al.. (2024). Collaborative multi-knowledge distillation under the influence of softmax regression representation. Multimedia Systems. 30(6). 1 indexed citations
6.
Xia, Yang, Yan Jin, Mian Chen, & Kangping Chen. (2023). Thermo-poroelastodynamic response of a borehole in a saturated porous medium subjected to a non-hydrostatic stress field. International Journal of Rock Mechanics and Mining Sciences. 170. 105422–105422. 2 indexed citations
7.
Wang, Yuanyuan, et al.. (2021). Study on crack dynamic evolution and damage-fracture mechanism of rock with pre-existing cracks based on acoustic emission location. Journal of Petroleum Science and Engineering. 201. 108420–108420. 80 indexed citations
8.
Xia, Yang, Shiming Wei, Yan Jin, & Kangping Chen. (2021). Self-diffusion flow and heat coupling model applicable to the production simulation and prediction of deep shale gas wells. Natural Gas Industry B. 8(4). 359–366. 3 indexed citations
9.
Wei, Shiming, Yang Xia, Yan Jin, Mian Chen, & Kangping Chen. (2018). Quantitative study in shale gas behaviors using a coupled triple-continuum and discrete fracture model. Journal of Petroleum Science and Engineering. 174. 49–69. 36 indexed citations
10.
Jiang, Hailong, Mian Chen, Yan Jin, & Kangping Chen. (2015). Importance of Gas Acceleration Near the Wellbore in Radial Compressible Porous Media Flows for a Vertical Gas Well. Transport in Porous Media. 110(1). 127–140. 3 indexed citations
11.
Jiang, Hai‐Long, Mian Chen, Yan Jin, & Kangping Chen. (2015). Analytical modeling of acceleration-induced conductivity damage in a propped hydraulic fracture of a high-pressure gas well. Journal of Natural Gas Science and Engineering. 26. 185–192. 7 indexed citations
12.
Jin, Yan, et al.. (2010). Pre-Caspian basin wells in salt-gypsum beds require an optimized drilling fluid. Oil & gas journal. 108(4). 46–53. 2 indexed citations
13.
Jin, Yakang, et al.. (2009). Depressant replaces mechanical method for removing blockage. Oil & gas journal. 107(41). 37–43. 2 indexed citations
14.
Hayes, Mark A., et al.. (2007). Liposomes Form Nanotubules and Long Range Networks in the Presence of Electric Field. Journal of Nanoscience and Nanotechnology. 7(7). 2283–2286. 10 indexed citations
15.
Chen, Kangping & D. G. Crighton. (1994). Instability of the large Reynolds number flow of a Newtonian fluid over a viscoelastic fluid. Physics of Fluids. 6(1). 152–163. 2 indexed citations
16.
Chen, Kangping. (1993). Wave formation in the gravity-driven low-Reynolds number flow of two liquid films down an inclined plane. Physics of Fluids A Fluid Dynamics. 5(12). 3038–3048. 50 indexed citations
17.
Chen, Kangping & Daniel D. Joseph. (1992). Elastic short wave instability in extrusion flows of viscoelastic liquids. Journal of Non-Newtonian Fluid Mechanics. 42(1-2). 189–211. 26 indexed citations
18.
Chen, Kangping & Daniel D. Joseph. (1991). Lubricated pipelining: stability of core–annular flow. Part 4. Ginzburg–Landau equations. Journal of Fluid Mechanics. 227. 587–615. 23 indexed citations
19.
Chen, Kangping & Daniel D. Joseph. (1990). Lubrication theory and long waves. University of Minnesota Digital Conservancy (University of Minnesota). 1 indexed citations
20.
Preziosi, Luigi, Kangping Chen, & Daniel D. Joseph. (1989). Lubricated pipelining: stability of core-annular flow. Journal of Fluid Mechanics. 201. 323–356. 165 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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